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Lex Rosetta: Transfer of Predictive Models across Languages, Jurisdictions, and Legal Domains

par Savelka, Jaromir;Westermann, Hannes;Benyekhlef, Karim;Alexander, Charlotte;Grant, Jayla;Restrepo Amariles, David ;El Hamdani, Rajaa;Meeùs, Sébastien ;Troussel, Aurore;Araszkiewicz, Michal;Ashley, Kevin;Ashley, Alexandra;Branting, Karl;Falduti, Mattia;Grabmair, Matthias;Haravsta, Jakub;Novotn'a, Tereza;Tippett, Elizabeth;Johnson, Shiwanni
Référence Proceedings of the Eighteenth International Conference on Artificial Intelligence and Law Proceedings of the Eighteenth International Conference on Artificial Intelligence and Law, Association for Computing Machinery, page (129–138)
Publication Publié, 2021

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Titre:	Lex Rosetta: Transfer of Predictive Models across Languages, Jurisdictions, and Legal Domains
Auteur:	Savelka, Jaromir; Westermann, Hannes; Benyekhlef, Karim; Alexander, Charlotte; Grant, Jayla; Restrepo Amariles, David; El Hamdani, Rajaa; Meeùs, Sébastien; Troussel, Aurore; Araszkiewicz, Michal; Ashley, Kevin; Ashley, Alexandra; Branting, Karl; Falduti, Mattia; Grabmair, Matthias; Haravsta, Jakub; Novotn'a, Tereza; Tippett, Elizabeth; Johnson, Shiwanni
Informations sur la publication:	Proceedings of the Eighteenth International Conference on Artificial Intelligence and Law Proceedings of the Eighteenth International Conference on Artificial Intelligence and Law, Association for Computing Machinery, page (129–138)
Statut de publication:	Publié, 2021
series:	ICAIL '21
Sujet CREF:	Intelligence artificielle
	Droit public
	Droit économique
Mots-clés:	multi-lingual sentence embeddings, adjudicatory decisions, annotation, document segmentation, transfer learning, domain adaptation
Langue:	Français
Identificateurs:	urn:isbn:9781450385268
	info:doi/10.1145/3462757.3466149